Sarah M. Larson

The Pacific Meridional Mode as an ENSO Precursor and Predictor in the North American Multimodel Ensemble

AbstractAlthough modeling and observational studies have highlighted a robust relationship between the Pacific meridional mode (PMM) and El Nino–Southern Oscillation (ENSO)—namely, that the PMM is often a precursor to El Nino events—it remains unclear if this relationship has any real predictive use. Bridging the gap between theory and practical application is essential, because the potential use of the PMM precursor as a supplemental tool for ENSO prediction has been implied but not yet implemented into a realistic forecast setting. In this paper, a suite of sea surface temperature hindcasts is utilized from the North American Multimodel Ensemble (NMME) prediction experiment between 1982 and 2010. The goal is first to assess the NMME’s ability to forecast the PMM precursor and second to examine the relationship between PMM and ENSO within a forecast framework. In terms of model performance, results are optimistic in that not only is PMM variability captured well by the multimodel ensemble mean, but it al...

An alternate approach to ensemble ENSO forecast spread: Application to the 2014 forecast

Evaluating the 2014 El Nino forecast as a “bust” may be tapping into a bigger issue, namely that forecast “overconfidence” from single-model ensembles could affect the retrospective assessment of El Nino–Southern Oscillation (ENSO) predictions. The present study proposes a new approach to quantifying an “expected” spread and uncertainty from noise-driven processes and supplementing these measures with actual ENSO forecasts. Expanding on a previously developed coupled model framework that isolates noise-driven ENSO-like errors, an experimental design is implemented to generate an expected December Nino-3.4 spread from March initial condition sea surface temperature errors that have similar structure to the 2014 and 2015 observed. Results reveal that the 2014 ENSO forecast falls within the expected uncertainty generated by ENSO-independent, forecast-independent, noise-driven errors.

Revisiting ENSO Coupled Instability Theory and SST Error Growth in a Fully Coupled Model

AbstractA coupled model framework is presented to isolate coupled instability induced SST error growth in the ENSO region. The modeling framework using CCSM4 allows for seasonal ensembles of initialized simulations that are utilized to quantify the spatial and temporal behavior of coupled instabilities and the associated implications for ENSO predictability. The experimental design allows for unstable growth of initial perturbations that are not prescribed, and several cases exhibit sufficiently rapid growth to produce ENSO events that do not require a previous ENSO event, large-scale wind trigger, or subsurface heat content precursor. Without these precursors, however, ENSO amplitude is reduced.The initial error growth exhibits strong seasonality with fastest growth during spring and summer and also dependence on the initialization month with the fastest growth occurring in the July ensemble. Peak growth precedes the peak error, and evidence suggests that the final state error may be sensitive to a sligh...